4.7 Article

Digital twin-driven rapid reconfiguration of the automated manufacturing system via an open architecture model

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2019.101895

Keywords

Digital twin; Reconfigurable manufacturing system; Open architecture; Cyber-physical system; Industrial internet of things; Smart manufacturing

Funding

  1. National Natural Science Foundation of China [51705091, 51675108]
  2. Science and Technology Planning Project of Guangdong Province of China [2019A050503010, 2019B090916002, 2019A1515011815]
  3. 2030 Innovation Megaprojects of China (Programme on New Generation Artificial Intelligence) [2018AAA0101700]
  4. National Key Research and Development Project [2019YFB1706200]
  5. Science and Technology Plan Project of Guangzhou [201804020092]
  6. Shenzhen Science and Technology Innovation Committee [JCY20170818100156260]
  7. Hong Kong Scholars Program [XJ201817]

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Increasing individualization demands in products call for high flexibility in the manufacturing systems to adapt changes. This paper proposes a novel digital twin-driven approach for rapid reconfiguration of automated manufacturing systems. The digital twin comprises two parts, the semi-physical simulation that maps data of the system and provides input data to the second part, which is optimization. The results of the optimization part are fed back to the semi-physical simulation for verification. Open-architecture machine tool (OAMT) is defined and developed as a new class of machine tools comprising a fixed standard platform and various individualized modules that can be added and rapidly swapped. Engineers can flexibly reconfigure the manufacturing system for catering to process planning by integrating personalized modules into its OAMTs. Key enabling techniques, including how to twin cyber and physical system and how to quickly bi-level program the production capacity and functionality of manufacturing systems to adapt rapid changes of products, are detailed. A physical implementation is conducted to verify the effectiveness of the proposed approach to achieving improved system performance while minimizing the overheads of the reconfiguration process by automating and rapidly optimizing it.

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